Fast "online" migration with Compressive Sensing
| Title | Fast "online" migration with Compressive Sensing |
| Publication Type | Conference |
| Year of Publication | 2015 |
| Authors | Felix J. Herrmann, Ning Tu, Ernie Esser |
| Conference Name | EAGE Annual Conference Proceedings |
| Month | 06 |
| Keywords | EAGE, LSRTM |
| Abstract | We present a novel adaptation of a recently developed relatively simple iterative algorithm to solve large-scale sparsity-promoting optimization problems. Our algorithm is particularly suitable to large-scale geophysical inversion problems, such as sparse least-squares reverse-time migration or Kirchoff migration since it allows for a tradeoff between parallel computations, memory allocation, and turnaround times, by working on subsets of the data with different sizes. Comparison of the proposed method for sparse least-squares imaging shows a performance that rivals and even exceeds the performance of state-of-the art one-norm solvers that are able to carry out least-squares migration at the cost of a single migration with all data. |
| Notes | (EAGE, Madrid) |
| URL | https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/herrmann2015EAGEfom/herrmann2015EAGEfom.html |
| DOI | 10.3997/2214-4609.201412942 |
| Presentation | |
| Citation Key | herrmann2015EAGEfom |